microsoft/markitdown
MarkItDown is a Python tool that converts various file formats into Markdown and integrates with LLM applications via an MCP server for enhanced text analysis and document processing.
Awesome MCP › Other MCP Servers
CodeGraphContext (CGC) is a powerful tool designed to bridge the gap between deep code graphs and AI context. It functions as both an MCP server and a CLI toolkit, allowing it to index local code into a graph database to provide enhanced context for AI assistants and human developers alike. The project supports comprehensive parsing and analysis for 12 programming languages, including Python, JavaScript, TypeScript, Java, C/C++, C#, Go, Rust, Ruby, PHP, Swift, and Kotlin. For each language, CGC extracts critical information such as functions, classes, methods, parameters, inheritance relationships, and function calls to construct a detailed code graph. Key features include efficient code indexing, advanced relationship analysis (e.g., callers, callees, class hierarchies), and the ability to load pre-indexed bundles for popular repositories. It also offers live file watching to automatically update the graph in real-time, an interactive setup wizard, and dual-mode operation as a standalone CLI or an MCP server. This flexibility allows developers to gain comprehensive code analysis or integrate it with their preferred AI IDEs via the Model Context Protocol. CGC supports two graph database backends: FalkorDB Lite for zero-config local development and Neo4j for larger-scale or production environments. It is currently being explored for static code analysis in AI assistants, graph-based project visualization, and dead code/complexity detection, running on Python 3.10-3.14.
https://github.com/Shashankss1205/CodeGraphContext
MarkItDown is a Python tool that converts various file formats into Markdown and integrates with LLM applications via an MCP server for enhanced text analysis and document processing.
A curated collection of Model Context Protocol (MCP) servers that enable AI models to securely interact with local and remote resources through standardized server implementations.
The Model Context Protocol Servers repository offers reference implementations and third-party integrations that demonstrate how MCP enables Large Language Models to securely access and interact with diverse tools and data sources.
World Monitor is an AI-powered, real-time global intelligence dashboard aggregating news and monitoring geopolitical and infrastructure data for unified situational awareness.
Headroom is a context compression layer for AI agents, reducing token usage by 60-95% while preserving accuracy, implemented as a library, proxy, and MCP server.
OmniRoute is a free AI gateway that connects various AI tools and models from over 230 providers through a single endpoint, featuring token compression, smart auto-fallback, and support for Model C...
This comprehensive curriculum teaches AI engineering from scratch, focusing on building AI algorithms, agents, and MCP servers hands-on, covering everything from mathematical foundations to autonom...
Open source, self-hostable SEO platform that exposes its keyword, rank, backlink and site-audit data to AI agents through an MCP server and a set of companion agent skills.